Solutions Consultant, Machine Learning

📋 Description

• • As a Solutions Consultant focused on Machine Learning at Cradle Bio, you will serve as the technical bridge between the company's AI-powered protein design platform and sophisticated biotech and pharmaceutical clients who are building advanced in-house ML capabilities. Your role is critical in translating complex technical capabilities into compelling value propositions that resonate with scientific and engineering audiences.
• • Day to day, you will own the technical discovery process with prospects by analyzing their computational infrastructure, ML workflows, and protein engineering goals; design and deliver tailored technical demonstrations for ML-savvy audiences including researchers and engineers; lead deep technical conversations with computational teams to establish credibility and address sophisticated inquiries; develop high-impact sales assets such as presentations and benchmarks that elevate Cradle’s technical storytelling; provide field-driven insights to product and ML teams to inform roadmap decisions; and collaborate with and mentor fellow Solutions Consultants to strengthen the team’s collective technical expertise.
• • Cradle Bio is a fast-growing, well-funded AI-driven biotechnology company headquartered with hubs in Zurich and Amsterdam, operating with a distributed workforce of approximately 75 employees. The company specializes in providing a software platform that leverages machine learning to enable rapid, scalable protein design and optimization for therapeutic, agricultural, food, and industrial applications. Backed by a strong track record of prior success and multi-year funding, Cradle emphasizes innovation, technical excellence, and an inclusive, high-performance culture.
• • In this role, you will deepen your expertise in applying machine learning to real-world scientific challenges, particularly in structural biology and protein engineering; refine your ability to communicate complex technical concepts to diverse stakeholders ranging from ML engineers to executive leaders; gain influence over product direction by feeding frontline insights into R&D processes; and develop mastery in technical sales and solution positioning within high-stakes, science-driven enterprise environments.